June 2023
Volume 64, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2023
Unpredictability of Axial Elongation in Infants undergoing Cataract Surgery
Author Affiliations & Notes
  • Arthur abrant
    Stanford Medicine, Stanford, California, United States
  • Isdin Oke
    Harvard University, Cambridge, Massachusetts, United States
  • Scott McClatchey
    University of California at San Diego Department of Ophthalmology at the Shiley Eye Institute, La Jolla, California, United States
  • Prithvi Mruthyunjaya
    Stanford Medicine, Stanford, California, United States
  • Darius M Moshfeghi
    Stanford Medicine, Stanford, California, United States
  • Cassie Ann Ludwig
    Stanford Medicine, Stanford, California, United States
  • Scott R Lambert
    Stanford Medicine, Stanford, California, United States
  • Footnotes
    Commercial Relationships   Arthur abrant Google, Code C (Consultant/Contractor); Isdin Oke None; Scott McClatchey None; Prithvi Mruthyunjaya Alcon, Code C (Consultant/Contractor), Aura Bioscience, Code C (Consultant/Contractor), Castle Bioscience, Code C (Consultant/Contractor); Darius Moshfeghi None; Cassie Ludwig None; Scott Lambert None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2023, Vol.64, 1212. doi:
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      Arthur abrant, Isdin Oke, Scott McClatchey, Prithvi Mruthyunjaya, Darius M Moshfeghi, Cassie Ann Ludwig, Scott R Lambert; Unpredictability of Axial Elongation in Infants undergoing Cataract Surgery. Invest. Ophthalmol. Vis. Sci. 2023;64(8):1212.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : It is difficult to predict future myopic shift in pediatric patients. Ocular biometric data is scarce for young children because acquiring keratometry and axial length measurements typically requires general anesthesia. This study leverages data from the Infant Aphakia Treatment Study (IATS) to evaluate the association between axial length elongation during infancy (age 0-1 years) and childhood (age 1-10 years).

Methods : We used biometric data from the IATS, which collected longitudinal keratometry and axial length measurements on infants (age 0-1) undergoing unilateral cataract surgery. First, we fit a logarithmic regression to model axial length as a function of age. Next, we construct two cohorts: fast infant growers (patients whose axial length change between cataract surgery and 1 year postoperatively exceeded our model's prediction) and slow infant growers (elongation less than model prediction). We then compared the future change in axial length (ages 1 to 5, 5 to 10, and 1 to 10 years) between slow and fast growers using student’s t-test.

Results : This study included 114 patients (114 phakic eyes, 57 aphakic eyes, 57 pseudophakic eyes). Axial length was fit by a logarithmic function (0.851 * log2(age in days) + 12.851) (Figure 1). The change in axial length between fast growers and slow growers was not significantly different between ages 1-5, 1-10, and 5-10 years (p values 0.53, 0.71, 0.95 respectively) (Figure 2). This finding remained true for sensitivity analyses (1) investigating the non-cataractous fellow eye and (2) comparing the 25th percentile fastest growers with the 25th percentile slowest growers. 50% of infants with fast axial elongation remained fast growers between age 1-10, whereas 60% of infants with slow axial elongation changed to fast growers.

Conclusions : Axial elongation follows a logarithmic pattern with respect to time. Accelerated axial elongation during infancy did not correlate with accelerated axial elongation during childhood years. Study limitations include a small sample size, inherent noise in EUA measurements, and a biased sample of infants who underwent cataract surgery. The lack of correlation will increase the complexity of building models to predict future refractive error. The underlying biological triggers that accelerate or decelerate axial elongation should be investigated further.

This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.

 

Modelling Axial Elongation with Time

Modelling Axial Elongation with Time

 

Axial Length change between slow and fast growers

Axial Length change between slow and fast growers

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